基于EEMD-ELM的输电线路温度预测模型
A Temperature Prediction Model for Transmission Lines Based on EEMD-ELD
王新涛 1郑强 2牟磊 2李宗 2赵建坤3
作者信息
- 1. 青岛电气工程安装有限公司,山东青岛 266000
- 2. 国网山东省电力公司青岛供电公司,山东青岛 266002
- 3. 内蒙古电力科学研究院,内蒙古呼和浩特 010020
- 折叠
摘要
受负载、环境温度、风速、太阳辐射等多种因素影响,采用单一模型对输电线路温度进行预测的准确度较低.文章提出基于集合经验模态分解(EEMD)-极限学习机(ELM)的输电线路温度预测模型,并进行了试验验证.试验结果表明,相较BP神经网络模型、SVM模型,文章提出的预测模型的预测准确度较高.
Abstract
Due to many factors such as load,ambient temperature,wind speed,solar radiation,etc.,the accuracy of using a single model to predict the transmission line temperature is low.A temperature prediction model of transmission line based on ensemble Empirical Mode decomposition(EEMD)and Extreme Learning Machine(ELM)is proposed and verified by experiments.The experimental results show that compared with BP neural network model and SVM model,the prediction accuracy of the proposed model is higher.
关键词
输电线路/温度/集合经验模态分解/极限学习机Key words
transmission lines/temperature/ensemble empirical mode decomposition/extreme learning machine引用本文复制引用
出版年
2024
NETL
NSTL
万方数据